152 related articles for article (PubMed ID: 21718813)
1. IPM: An integrated protein model for false discovery rate estimation and identification in high-throughput proteomics.
Higdon R; Reiter L; Hather G; Haynes W; Kolker N; Stewart E; Bauman AT; Picotti P; Schmidt A; van Belle G; Aebersold R; Kolker E
J Proteomics; 2011 Dec; 75(1):116-21. PubMed ID: 21718813
[TBL] [Abstract][Full Text] [Related]
2. A new estimation of protein-level false discovery rate.
Wu G; Wan X; Xu B
BMC Genomics; 2018 Aug; 19(Suppl 6):567. PubMed ID: 30367581
[TBL] [Abstract][Full Text] [Related]
3. SPIRE: Systematic protein investigative research environment.
Kolker E; Higdon R; Morgan P; Sedensky M; Welch D; Bauman A; Stewart E; Haynes W; Broomall W; Kolker N
J Proteomics; 2011 Dec; 75(1):122-6. PubMed ID: 21609792
[TBL] [Abstract][Full Text] [Related]
4. Meta-analysis for protein identification: a case study on yeast data.
Higdon R; Haynes W; Kolker E
OMICS; 2010 Jun; 14(3):309-14. PubMed ID: 20569183
[TBL] [Abstract][Full Text] [Related]
5. False discovery rates in spectral identification.
Jeong K; Kim S; Bandeira N
BMC Bioinformatics; 2012; 13 Suppl 16(Suppl 16):S2. PubMed ID: 23176207
[TBL] [Abstract][Full Text] [Related]
6. Transferred subgroup false discovery rate for rare post-translational modifications detected by mass spectrometry.
Fu Y; Qian X
Mol Cell Proteomics; 2014 May; 13(5):1359-68. PubMed ID: 24200586
[TBL] [Abstract][Full Text] [Related]
7. A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets.
Savitski MM; Wilhelm M; Hahne H; Kuster B; Bantscheff M
Mol Cell Proteomics; 2015 Sep; 14(9):2394-404. PubMed ID: 25987413
[TBL] [Abstract][Full Text] [Related]
8. Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry.
Reiter L; Claassen M; Schrimpf SP; Jovanovic M; Schmidt A; Buhmann JM; Hengartner MO; Aebersold R
Mol Cell Proteomics; 2009 Nov; 8(11):2405-17. PubMed ID: 19608599
[TBL] [Abstract][Full Text] [Related]
9. Protein Probability Model for High-Throughput Protein Identification by Mass Spectrometry-Based Proteomics.
Prieto G; Vázquez J
J Proteome Res; 2020 Mar; 19(3):1285-1297. PubMed ID: 32037837
[TBL] [Abstract][Full Text] [Related]
10. Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.
Keich U; Kertesz-Farkas A; Noble WS
J Proteome Res; 2015 Aug; 14(8):3148-61. PubMed ID: 26152888
[TBL] [Abstract][Full Text] [Related]
11. False Discovery Rate Estimation for Hybrid Mass Spectral Library Search Identifications in Bottom-up Proteomics.
Burke MC; Zhang Z; Mirokhin YA; Tchekovskoi DV; Liang Y; Stein SE
J Proteome Res; 2019 Sep; 18(9):3223-3234. PubMed ID: 31364354
[TBL] [Abstract][Full Text] [Related]
12. Unbiased False Discovery Rate Estimation for Shotgun Proteomics Based on the Target-Decoy Approach.
Levitsky LI; Ivanov MV; Lobas AA; Gorshkov MV
J Proteome Res; 2017 Feb; 16(2):393-397. PubMed ID: 27959540
[TBL] [Abstract][Full Text] [Related]
13. A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification.
Tu C; Shen S; Sheng Q; Shyr Y; Qu J
J Proteomics; 2017 Jan; 152():276-282. PubMed ID: 27903464
[TBL] [Abstract][Full Text] [Related]
14. An easy-to-use Decoy Database Builder software tool, implementing different decoy strategies for false discovery rate calculation in automated MS/MS protein identifications.
Reidegeld KA; Eisenacher M; Kohl M; Chamrad D; Körting G; Blüggel M; Meyer HE; Stephan C
Proteomics; 2008 Mar; 8(6):1129-37. PubMed ID: 18338823
[TBL] [Abstract][Full Text] [Related]
15. Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines.
Jones AR; Siepen JA; Hubbard SJ; Paton NW
Proteomics; 2009 Mar; 9(5):1220-9. PubMed ID: 19253293
[TBL] [Abstract][Full Text] [Related]
16. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.
Nesvizhskii AI
J Proteomics; 2010 Oct; 73(11):2092-123. PubMed ID: 20816881
[TBL] [Abstract][Full Text] [Related]
17. Using the entrapment sequence method as a standard to evaluate key steps of proteomics data analysis process.
Feng XD; Li LW; Zhang JH; Zhu YP; Chang C; Shu KX; Ma J
BMC Genomics; 2017 Mar; 18(Suppl 2):143. PubMed ID: 28361671
[TBL] [Abstract][Full Text] [Related]
18. Peptide identifications and false discovery rates using different mass spectrometry platforms.
Anapindi KDB; Romanova EV; Southey BR; Sweedler JV
Talanta; 2018 May; 182():456-463. PubMed ID: 29501178
[TBL] [Abstract][Full Text] [Related]
19. An automated proteomic data analysis workflow for mass spectrometry.
Pendarvis K; Kumar R; Burgess SC; Nanduri B
BMC Bioinformatics; 2009 Oct; 10 Suppl 11(Suppl 11):S17. PubMed ID: 19811682
[TBL] [Abstract][Full Text] [Related]
20. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.
Lin L; Zheng J; Yu Q; Chen W; Xing J; Chen C; Tian R
J Proteomics; 2018 Mar; 174():9-16. PubMed ID: 29278786
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]